When it comes to groups that work together to get a job done, ants have pretty much got the process perfected. That’s why computer scientist Marco Dorigo studied the creatures’ behavior, and created his Ant Colony Optimization
model – an algorithmic technique that can be applied to human endeavors, when efficiency is the order of the day. Scientists from Germany’s Fraunhofer Institute for Material Flow and Logistics have now applied these algorithms to a swarm of 50 autonomous shuttle robots working in a parts warehouse, in an effort to create a new and better type of materials-handling system.
Ant colonies aren't called superorganisms for nothing. In some species, millions of individuals can act as a single entity to protect and feed the colony. This behavior has led to over 200 different species being called "Army Ants", so in a way it's no surprise that these mechanisms have been used for the basis of new software that helps troops to define the best path within a battle field.
In looking for highly efficient ways to solve complex problems, we've often seen researchers mimic the solutions found by nature over billions of years: smart fabrics inspired by pine cones
, spectrum analyzers modeled after the human ear
and powerful search-and-optimization genetic and evolutionary algorithms, to name just a few. The latest piece of news comes from Wake Forest University, where the group dynamics of ant colonies have inspired security software to fight computer worms and other threats.